1. Field of the Invention
The present invention relates to information processing apparatuses and the like that process values acquired from semiconductor manufacturing apparatuses.
2. Description of Related Art
As a semiconductor manufacturing apparatus for manufacturing a semiconductor device, for example, there is a heat treatment apparatus for performing a heat treatment such as a film-forming process, an oxidizing process, or a diffusion process, on a treatment target including a semiconductor such as semiconductor wafers.
In a heat treatment apparatus and the like, typically, a heat treatment is performed by controlling an item such as treatment temperature, treatment pressure, or gas flow rate so as to match a set value referred to as recipe, which is a value for setting a condition of the treatment.
For example, regarding such a heat treatment apparatus, there is a technique for controlling the electric power of a heater, using estimated values that are obtained by arranging multiple temperature sensors in a reaction furnace, and sequentially estimating the temperature of semiconductor wafers using a thermal model (mathematical model) based on factors such as the output from the temperature sensors and the electric power supplied to the heater (see JP 2002-25997A (e.g., page 1, FIG. 1), for example). According to such a technique, the temperature of semiconductor wafers in a non-contact state can be relatively accurately estimated, and thus the treatment temperature can be precisely controlled.
In a heat treatment apparatus as described above, it is judged whether or not the apparatus is properly operating, or whether or not a desired treatment is properly performed, by acquiring values indicating a state during a treatment, such as treatment temperature, treatment pressure, and electric power of a heater when a treatment is actually performed, and monitoring these values. For example, when in a single apparatus, results of a treatment performed for multiple times using the same recipe are plotted on a graph in the course of time, time-series deterioration or the like of the functions of the heat treatment apparatus can be judged.
However, regarding results of treatments performed using different set values, values acquired from the heat treatment apparatus are typically different from each other, and thus values obtained for the respective set values are managed using, for example, different control charts. Thus, it is not possible to monitor the treatment results simultaneously. In order to monitor the treatment results, it is necessary to switch the display of the control charts. Accordingly, there is a problem in that such operations take an inordinate amount of effort, and operations for monitoring are complicated.
Furthermore, since management is performed on the different control charts, it is difficult to simultaneously compare values of the treatment results with each other. Even if values obtained using the different set values are displayed in one system of coordinates, graphs of the values obtained using the different set values are plotted at positions that are away from each other, and thus there is a problem in that it is difficult to compare these values with each other.
Furthermore, typically, it is judged whether or not an apparatus or a treatment performed by an apparatus is properly operating, by setting a threshold value or the like for a value acquired from a heat treatment apparatus or the like in advance, and judging whether the value acquired from the heat treatment apparatus or the like is equal to or larger than the threshold value, or is smaller than the threshold value. When set values are different from each other, acquired values obtained from the heat treatment apparatus or the like are also different from each other. Thus, it is necessary to set threshold values in advance for the respective set values. Accordingly, there is a problem in that a process of setting threshold values takes an effort and time.
Furthermore, in a conventional information processing apparatus, it is difficult to display values, for example, in different value units or value ranges acquired from the semiconductor manufacturing apparatus in a superimposed manner, or to compare these values with each other. For example, even if internal temperature values acquired from the semiconductor manufacturing apparatus and electric power values of a heater inside the semiconductor manufacturing apparatus are plotted in a simply superimposed manner on a graph, it is difficult to accurately compare the values with each other because their units and the like are different from each other.
Furthermore, it is substantially not possible to apply multivariate analysis on such values in different units or the like without any processing, because even if applied, obtained values vary depending on how the units are taken.
Therefore, it is conceivable to perform so-called standardization on values acquired from the semiconductor manufacturing apparatus. The standardization refers to a process in which the values are converted into values that are not affected by how the units are taken, by converting the units of the values such that the average value and the standard deviation are set to specified values, for example. By performing such standardization, information expressed in different units can be compared with each other and can be analyzed using multivariate analysis. Typically, the standardization is performed such that the average value is 0 and that the standard deviation is 1. More specifically, the standardization is performed by calculating the formula “(value indicating a state−average value)/standard deviation”, on each value indicating the state of the semiconductor manufacturing apparatus, acquired from the semiconductor manufacturing apparatus.
Such conventional standardization is effective in a case where data is normally-distributed, but there is a problem in that the standardization is not suitable as a process performed in a case where data is not normally-distributed.
For example, a case is described in which multivariate analysis is performed on state values in different measurement units. Typically, in multivariate analysis, standardization is performed as a preparation process such that there is no influence of the units and the like. At that time, there may be a case in which most state values are concentrated in the vicinity of a particular value, and only one value is significantly away from the particular value. In this case, there is a problem in that even if the one value is in the range of normal values as a value acquired from the semiconductor manufacturing apparatus, when the above-described standardization using the standard deviation is performed, the value may be judged to be a value that is significantly different from the others, as a result of the multivariate analysis.
Furthermore, in a case where values obtained by performing the standardization in this manner on values in different measurement units are plotted in a superimposed manner on a graph or the like or compared with each other, the standardization is performed on the values in different measurement units themselves such that there is no influence of the measurement units. However, when threshold values and the like are set for the respective values, even when the standardization is performed on the threshold values and the like, different threshold values are obtained. Consequently, it is necessary to evaluate values obtained by performing the standardization on values in different measurement units, using different threshold values. Thus, comparison and the like between state values cannot be said to be sufficiently easy, and there is a problem in that the effects of the standardization cannot be achieved.
As described above, conventionally, there is a problem in that values in different units or the like cannot be converted into appropriate values that do not depend on measurement units and that are suitable for data analysis such as multivariate analysis or comparison between the values.